多点地质统计学建模参数敏感性分析Sensitivity Analyses of Parameters for Multiple-point Geostatistics Modeling
文子桃,林承焰,陈仕臻,张建兴
摘要(Abstract):
与基于像元的两点模拟和基于目标的模拟相比,多点地质统计学能较好地忠实于硬数据(井数据)和再现复杂的地质体形态。在介绍多点模拟算法(Snesim)实现流程的基础上,对Snesim算法中重要的输入参数进行了敏感性分析,结果表明:目标比率越接近训练图像的边缘相概率,模拟效果越好;目标比率一定时,提高伺服参数可使模拟相的比率更接近目标体,但以损失相结构信息为代价;搜索邻域的设计、网格级数的选择取决于训练图像的大小以及需重现的结构信息;此外,在一个较小的数据事件重复数下,随着最大条件数据的增加,其结构信息的再现效果越好,所需机时则呈线性增加。可见,参数设置对多点地质建模中模拟效果的好坏至关重要。
关键词(KeyWords): 地质建模;多点模拟算法;训练图像;目标比率;搜索邻域;多级网格
基金项目(Foundation): 国家科技重大专项“复杂油气藏精细表征及剩余油分布预测”(编号:2011ZX05009-003)
作者(Author): 文子桃,林承焰,陈仕臻,张建兴
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